A comparative bibliometric analysis of Omicron and Delta variants during the COVID-19 pandemic.

BACKGROUND: To compare the research hotspots of infections with the Delta and Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the coronavirus disease 2019 (COVID-19) pandemic and to identify future research trends. METHODS: Studies about Delta and Omicron variant infections published over the last 3 years were retrieved from the Web of Science (WoS) database. A comparative bibliometric analysis was conducted through machine learning and visualization tools, including VOSviewer, Bibliographic Item Co-Occurrence Matrix Builder, and Graphical Clustering Toolkit. Research hotspots and trends in the field were analyzed, and the contributions and collaborations of countries, institutions, and authors were documented. A cross-sectional analysis of the relevant studies registered at ClinicalTrials.gov was also performed to clarify the direction of future research. RESULTS: A total of 1,787 articles distributed in 107 countries and 374 publications from 77 countries focused on the Delta and Omicron variants were included in our bibliometric analysis. The top five productive countries in both variants were the USA, China, the UK, India, and Germany. In 5,999 and 1,107 keywords identified from articles on the Delta and Omicron, the top two frequent keywords were the same: "COVID-19" (occurrence: 713, total link strength: 1,525 in Delta; occurrence: 137, total link strength: 354 in Omicron), followed by "SARS-CoV-2" (occurrence: 553, total link strength: 1,478 in Delta; occurrences 132, total link strength: 395 in Omicron). Five theme clusters from articles on Delta variant were identified: transmission, molecular structure, activation mode, epidemiology, and co-infection. While other three theme clusters were recognized for the Omicron variant: vaccine, human immune response, and infection control. Meanwhile, 21 interventional studies had been registered up to April 2022, most of which aimed to evaluate the immunogenicity and safety of different kinds of vaccines in various populations. CONCLUSIONS: Publications and clinical trials related to COVID-19 increased annually. As the first comparative bibliometric analysis for Delta and Omicron variants, we noticed that the relevant research trends have shifted from vaccine development to infection control and management of complications. The ongoing clinical studies will verify the safety and efficacy of promising drugs.

A bibliometric analysis of the application of artificial intelligence to advance individualized diagnosis and treatment of critical illness.

Background: Artificial intelligence (AI) has been extensively applied in the individualized diagnosis and treatment of critical illness, and numerous studies have been published on this topic. Therefore, a bibliometric analysis of these publications should be performed to provide a direction of hot topics and future research trends. Methods: A bibliometric analysis was performed on the research articles to identify the hot topics and any unsolved issues regarding the use of AI in individualized diagnosis and treatment of critical illness. Articles published from January 2011 to December 2021 were retrieved from the Web of Science (WOS) core collection database for bibliometric analysis, and a cross-sectional analysis of the relevant studies that had been registered at ClinicalTrials.gov was also conducted. Results: The number of articles published showed an annually increasing trend, with a worldwide geographic distribution over the past decade. Ultimately, 427 research articles were included in the bibliometric analysis. The relevant articles were divided into four separate clusters that focused on AI application aspects, prediction model establishment, coronavirus disease 2019 (COVID-19) treatment and outcome assessments, respectively. "Machine learning" was the most frequent keyword (147 occurrences, 165 links, and 395 total link strengths) followed by "risk", "models", and "mortality". With 205 articles, the United States of America (USA) had interacted the most with other countries (20 links, and 94 total link strength), while the domestic research institutes in China had infrequently collaborated with others. Approximately 130 trials focusing on the application of AI in the intensive care unit (ICU) and emergency department (ED) had been registered at ClinicalTrial.gov, and most of them (n=71, 54.6%) were interventional. The main research objectives of these trials were to provide decision making assistance and establish prediction models. However, only 3.8% (5 trials) of them had reached exact conclusions which favored the application of AI. Conclusions: The application of AI has raised great interest in critical illness and has mainly been focused on decision making assistance and prediction model establishment. Cooperation between agencies engaged in AI research needs to be strengthened. An increasing number of trials have been registered at ClinicalTrial.gov, and the results of them are promising. Keywords: Bibliometric analysis; artificial intelligence (AI); individualized diagnosis; critical care medicine; emergency department (ED).

A bibliometric analysis of infectious diseases in patients with liver transplantation in the last decade.

BACKGROUND: A bibliometric analysis was performed to reveal the current status of investigations in infectious diseases in patients with liver transplantation (LT) and to prioritize future research needs. METHODS: The present study comprehensively retrieved publications relevant to infectious diseases in LT recipients published between 2010 and 2020. The search was conducted on the Web of Science (WoS) database. A bibliometric analysis was conducted through machine learning and visualization tools, including VOSviewer, Bibliographic Item Co-Occurrence Matrix Builder, and Graphical Clustering Toolkit. Research hotspots and trends in the field were assessed, while the contributions and collaborations of countries, institutions, and authors were documented. RESULTS: A total of 691 publications were analyzed. Research output sharply increased in 2015, with a fast drop afterward. "Liver transplantation" was the most frequent keyword, with strong links to "hepatitis C virus" and "infection". Study areas included risk factors of infectious diseases in LT recipients, pathogens causing post-transplantation infections, antibacterial therapy and prophylaxis for peritransplant infection complications, living donor LT, and pediatric LT. The efficacy and safety of direct-acting antivirals (DAAs) for hepatitis C virus (HCV) infection among liver transplant recipients has attracted recent research interest. Didier Samuel was the most productive author, while Xavier Forns was the top-cited author. Shanghai Jiao Tong University was the most productive contributor, and Gilead Sciences was the most cited organization. Moreover, the USA was the greatest contributor. Gastroenterology was the most cited journal, while Liver Transplantation was the most prolific journal. CONCLUSIONS: This bibliometric analysis will better understand the research status of infectious complications in LT recipients and forecast future research trends. Priority should be given to identifying risk factors for peritransplantation infections and effective treatments against infectious complications in the coming years.

Quality Management for Point-Of-Care Testing of Pathogen Nucleic Acids: Chinese Expert Consensus.

COVID-19 continues to circulate globally in 2021, while under the precise policy implementation of China's public health system, the epidemic was quickly controlled, and society and the economy have recovered. During the pandemic response, nucleic acid detection of SARS-CoV-2 has played an indispensable role in the first line of defence. In the cases of emergency operations or patients presenting at fever clinics, nucleic acid detection is required to be performed and reported quickly. Therefore, nucleic acid point-of-care testing (POCT) technology for SARS-CoV-2 identification has emerged, and has been widely carried out at all levels of medical institutions. SARS-CoV-2 POCT has served as a complementary test to conventional polymerase chain reaction (PCR) batch tests, thus forming an experimental diagnosis platform that not only guarantees medical safety but also improves quality services. However, in view of the complexity of molecular diagnosis and the biosafety requirements involved, pathogen nucleic acid POCT is different from traditional blood-based physical and chemical index detection. No guidelines currently exist for POCT quality management, and there have been inconsistencies documented in practical operation. Therefore, Shanghai Society of Molecular Diagnostics, Shanghai Society of Laboratory Medicine, Clinical Microbiology Division of Shanghai Society of Microbiology and Shanghai Center for Clinical Laboratory have cooperated with experts in laboratory medicine to generate the present expert consensus. Based on the current spectrum of major infectious diseases in China, the whole-process operation management of pathogen POCT, including its application scenarios, biosafety management, personnel qualification, performance verification, quality control, and result reporting, are described here. This expert consensus will aid in promoting the rational application and robust development of this technology in public health defence and hospital infection management.

Evaluation of Positive End-Expiratory Pressure Strategies in Patients With Coronavirus Disease 2019-Induced Acute Respiratory Distress Syndrome.

Background: Different positive end-expiratory pressure (PEEP) strategies are available for subjects with coronavirus disease 2019 (COVID-19)-induced acute respiratory distress syndrome (ARDS) requiring invasive mechanical ventilation. We aimed to evaluate three conventional PEEP strategies on their effects on respiratory mechanics, gas exchanges, and hemodynamics. Methods: This is a prospective, physiologic, multicenter study conducted in China. We recruited 20 intubated subjects with ARDS and confirmed COVID-19. We first set PEEP by the ARDSnet low PEEP-fraction of inspired oxygen (FIO2) table. After a recruitment maneuver, PEEP was set at 15, 10, and 5 cm H2O for 10 min, respectively. Among these three PEEP levels, best-compliance PEEP was the one providing the highest respiratory system compliance; best-oxygenation PEEP was the one providing the highest PaO2 (partial pressure of arterial oxygen)/FIO2. Results: At each PEEP level, we assessed respiratory mechanics, arterial blood gas, and hemodynamics. Among three PEEP levels, plateau pressure, driving pressure, mechanical power, and blood pressure improved with lower PEEP. The ARDSnet low PEEP-FIO2 table and the best-oxygenation strategies provided higher PEEP than the best-compliance strategy (11 ± 6 cm H2O vs. 11 ± 3 cm H2O vs. 6 ± 2 cm H2O, p = 0.001), leading to higher plateau pressure, driving pressure, and mechanical power. The three PEEP strategies were not significantly different in gas exchange. The subgroup analysis showed that three PEEP strategies generated different effects in subjects with moderate or severe ARDS (n = 12) but not in subjects with mild ARDS (n = 8). Conclusions: In our cohort with COVID-19-induced ARDS, the ARDSnet low PEEP/FIO2 table and the best-oxygenation strategies led to higher PEEP and potentially higher risk of ventilator-induced lung injury than the best-compliance strategy. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT04359251.

Efficacy and safety of current therapeutic options for COVID-19 - lessons to be learnt from SARS and MERS epidemic: A systematic review and meta-analysis.

The rapidly progressing of coronavirus disease 2019 (COVID-19) pandemic has become a global concern. This meta-analysis aimed at evaluating the efficacy and safety of current option of therapies for severe acute respiratory syndrome (SARS), Middle Eastern respiratory syndrome (MERS) besides COVID-19, in an attempt to identify promising therapy for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected patients. We searched PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), and WANFANG DATA for randomized controlled trials (RCTs), prospective cohort, and retrospective cohort studies that evaluated therapies (hydroxychloroquine, lopinavir/ritonavir-based therapy, and ribavirin-based therapy, etc.) for SARS, MERS, and COVID-19. The primary outcomes were mortality, virological eradication and clinical improvement, and secondary outcomes were improvement of symptoms and chest radiography results, incidence of acute respiratory disease syndrome (ARDS), utilization of mechanical ventilation, and adverse events (AEs). Summary relative risks (RRs) and 95% confidence intervals (CIs) were calculated using random-effects models, and the quality of evidence was appraised using GRADEpro. Eighteen articles (5 RCTs, 2 prospective cohort studies, and 11 retrospective cohort studies) involving 4,941 patients were included. Compared with control treatment, anti-coronary virus interventions significantly reduced mortality (RR 0.65, 95% CI 0.44-0.96; I2 = 81.3%), remarkably ameliorate clinical improvement (RR 1.52, 95% CI 1.05-2.19) and radiographical improvement (RR 1.62, 95% CI 1.11-2.36, I2 = 11.0 %), without manifesting clear effect on virological eradication, incidence of ARDS, intubation, and AEs. Subgroup analyses demonstrated that the combination of ribavirin and corticosteroids remarkably decreased mortality (RR 0.43, 95% CI 0.27-0.68). The lopinavir/ritonavir-based combination showed superior virological eradication and radiographical improvement with reduced rate of ARDS. Likewise, hydroxychloroquine improved radiographical result. For safety, ribavirin could induce more bradycardia, anemia and transaminitis. Meanwhile, hydroxychloroquine could increase AEs rate especially diarrhea. Overall, the quality of evidence on most outcomes were very low. In conclusion, although we could not draw a clear conclusion for the recommendation of potential therapies for COVID-19 considering the very low quality of evidence and wide heterogeneity of interventions and indications, our results may help clinicians to comprehensively understand the advantages and drawbacks of each anti-coronavirus agents on efficacy and safety profiles. Lopinavir/ritonavir combinations might observe better virological eradication capability than other anti-coronavirus agents. Conversely, ribavirin might cause more safety concerns especially bradycardia. Thus, large RCTs objectively assessing the efficacy of antiviral therapies for SARS-CoV-2 infections should be conducted with high priority.

A simple nomogram for predicting failure of non-invasive respiratory strategies in adults with COVID-19: a retrospective multicentre study.

BACKGROUND: Non-invasive respiratory strategies (NIRS) including high-flow nasal cannula (HFNC) and non-invasive ventilation (NIV) have become widely used in patients with COVID-19 who develop acute respiratory failure. However, use of these therapies, if ineffective, might delay initiation of invasive mechanical ventilation (IMV) in some patients. We aimed to determine early predictors of NIRS failure and develop a simple nomogram and online calculator that can identify patients at risk of NIRS failure. METHODS: We did a retrospective, multicentre observational study in 23 hospitals designated for patients with COVID-19 in China. Adult patients (≥18 years) with severe acute respiratory syndrome coronavirus 2 infection and acute respiratory failure receiving NIRS were enrolled. A training cohort of 652 patients (21 hospitals) was used to identify early predictors of NIRS failure, defined as subsequent need for IMV or death within 28 days after intensive care unit admission. A nomogram was developed by multivariable logistic regression and concordance statistics (C-statistics) computed. C-statistics were validated internally by cross-validation in the training cohort, and externally in a validation cohort of 107 patients (two hospitals). FINDINGS: Patients were enrolled between Jan 1 and Feb 29, 2020. NIV failed in 211 (74%) of 286 patients and HFNC in 204 (56%) of 366 patients in the training cohort. NIV failed in 48 (81%) of 59 patients and HFNC in 26 (54%) of 48 patients in the external validation cohort. Age, number of comorbidities, respiratory rate-oxygenation index (ratio of pulse oximetry oxygen saturation/fraction of inspired oxygen to respiratory rate), Glasgow coma scale score, and use of vasopressors on the first day of NIRS in the training cohort were independent risk factors for NIRS failure. Based on the training dataset, the nomogram had a C-statistic of 0·80 (95% CI 0·74-0·85) for predicting NIV failure, and a C-statistic of 0·85 (0·82-0·89) for predicting HFNC failure. C-statistic values were stable in both internal validation (NIV group mean 0·79 [SD 0·10], HFNC group mean 0·85 [0·07]) and external validation (NIV group value 0·88 [95% CI 0·72-0·96], HFNC group value 0·86 [0·72-0·93]). INTERPRETATION: We have developed a nomogram and online calculator that can be used to identify patients with COVID-19 who are at risk of NIRS failure. These patients might benefit from early triage and more intensive monitoring. FUNDING: Ministry of Science and Technology of the People's Republic of China, Key Research and Development Plan of Jiangsu Province, Chinese Academy of Medical Sciences.

Current therapeutic options for coronavirus disease 2019 (COVID-19)-lessons learned from severe acute respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS) therapy: a systematic review protocol.

BACKGROUND: Coronavirus disease 2019 (COVID-19), also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, first manifested in December 2019, and spread rapidly worldwide. Facing this lethal disease, there is an urgent need to develop potent therapies against SARS-CoV-2 infection. SARS-CoV-2 phylogenetically and symptomatically resembles SARS-CoV and Middle East Respiratory Syndrome Coronavirus (MERS-CoV). Numerous agents have been utilised during the severe acute respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS) epidemics, which may show some benefit against SARS-CoV-2. METHODS: MEDLINE, EMBASE, Cochrane Library, CBM Disc, China National Knowledge Infrastructure, Wanfang Data, and the China Science and Technology Journal Database will be searched. Manual searches will be conducted by searching pre-printing websites, clinical trial registers, and screening the reference lists of inclusive studies. The screening of all citations and the selection of inclusive articles will be conducted by two reviewers. Randomised controlled trials (RCTs) and controlled cohort studies reporting antiviral therapies, including ribavirin, remdesivir, lopinavir/ritonavir, arbidol, chloroquine, hydroxychloroquine, and interferon, for SARS, MERS, and COVID-19 will be included. The primary outcomes will be mortality, incidence of acute respiratory distress syndrome, and utilisation of mechanical ventilation and intensive care unit admission. The secondary outcomes will be improvement in symptoms and chest radiography results, virus clearance, changes in blood test results, and serum tests. The quality of the retrieved RCTs and observational studies will be appraised according to the Cochrane risk of bias tool and the Newcastle-Ottawa Scale, respectively. If feasible, we will perform a fixed- or random-effects meta-analysis. DISCUSSION: This systematic review and meta-analysis will summarise all the available evidence for the efficacy and safety of current therapeutic options in SARS-CoV, MERS-CoV, or SARS-CoV-2-infected patients. The findings of this study may inform subsequent antiviral interventions for patients with COVID-19. STUDY REGISTRATION: The protocol of this study has been submitted to the PROSPERO platform (https://www.crd.york.ac.uk/PROSPERO/), and the registration number is CRD42020168639.

Identification of risk factors for mortality associated with COVID-19.

OBJECTIVES: Coronavirus Disease 2019 (COVID-19) has become a pandemic outbreak. Risk stratification at hospital admission is of vital importance for medical decision making and resource allocation. There is no sophisticated tool for this purpose. This study aimed to develop neural network models with predictors selected by genetic algorithms (GA). METHODS: This study was conducted in Wuhan Third Hospital from January 2020 to March 2020. Predictors were collected on day 1 of hospital admission. The primary outcome was the vital status at hospital discharge. Predictors were selected by using GA, and neural network models were built with the cross-validation method. The final neural network models were compared with conventional logistic regression models. RESULTS: A total of 246 patients with COVID-19 were included for analysis. The mortality rate was 17.1% (42/246). Non-survivors were significantly older (median (IQR): 69 (57, 77) vs. 55 (41, 63) years; p < 0.001), had higher high-sensitive troponin I (0.03 (0, 0.06) vs. 0 (0, 0.01) ng/L; p < 0.001), C-reactive protein (85.75 (57.39, 164.65) vs. 23.49 (10.1, 53.59) mg/L; p < 0.001), D-dimer (0.99 (0.44, 2.96) vs. 0.52 (0.26, 0.96) mg/L; p < 0.001), and α-hydroxybutyrate dehydrogenase (306.5 (268.75, 377.25) vs. 194.5 (160.75, 247.5); p < 0.001) and a lower level of lymphocyte count (0.74 (0.41, 0.96) vs. 0.98 (0.77, 1.26) × 109/L; p < 0.001) than survivors. The GA identified a 9-variable (NNet1) and a 32-variable model (NNet2). The NNet1 model was parsimonious with a cost on accuracy; the NNet2 model had the maximum accuracy. NNet1 (AUC: 0.806; 95% CI [0.693-0.919]) and NNet2 (AUC: 0.922; 95% CI [0.859-0.985]) outperformed the linear regression models. CONCLUSIONS: Our study included a cohort of COVID-19 patients. Several risk factors were identified considering both clinical and statistical significance. We further developed two neural network models, with the variables selected by using GA. The model performs much better than the conventional generalized linear models.

A bibliometric analysis using VOSviewer of publications on COVID-19.

BACKGROUND: As a global pandemic, COVID-19 has aroused great concern in the last few months and a growing number of related researches have been published. Therefore, a bibliometric analysis of these publications may provide a direction of hot topics and future research trends. METHODS: The global literatures about COVID-19 published between 2019 and 2020 were scanned in the Web of Science collection database. "COVID-19" "Novel Coronavirus" "2019-nCoV" and "SARS-CoV-2" were used as the keywords to reach the relevant publications. VOSviewer was applied to perform the bibliometric analysis of these articles. RESULTS: Totally 3,626 publications on the topic of COVID-19 were identified and "COVID-19" with a total link strength of 2,649 appeared as the most frequent keyword, which had a strong link to "pneumonia" and "epidemiology". The mean citation count of the top 100 most cited articles was 96 (range, 26-883). Most of them were descriptive studies and concentrated on the clinical features. The highest-ranking journal was British medical journal with 211 publications and the most cited journal was Lancet with 2,485 citation counts. Eleven articles written by Christian Drosten from Berlin Institute of Virology have been cited for 389 times and 40 articles from Chinese Academy of Sciences have been cited for 1,597 times which are the most cited author and organization. The number of collaborators with China is 44 and the total link strength is 487. The main partners of China are USA, England and Germany. The published literatures have focused on three topics: disease management, clinical features and pathogenesis. CONCLUSIONS: The current growth trends predict a large increase in the number of global publications on COVID-19. China made the most outstanding contribution within this important field. Disease treatment, spike protein and vaccine may be hotspots in the future.